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MindDomain: An Interoperability Tool to Generate Domain Models Through Mind Maps

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Computational Science and Its Applications -- ICCSA 2016 (ICCSA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9789))

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Abstract

Requirements engineering establishes that requirements definition process must be applied to obtain, validate and maintain one or more requirement documents. This process handles different stakeholders expectations and viewpoints, among them, the software designer whose responsibility is to create software models from information provided by domain experts and business specialist. However, due to knowledge differences between stakeholder’s technical dialects, communication problems are constant, generating inconsistencies between the conceptual model and the problem to be solved. To help solving these issues an agile and cognitive modeling based approach supported by MDA based tools is proposed promoting better consistency between requirements and the conceptual models, guaranteed by specifying a mind map that serves as the basis for translating requirements to domain models, represented by the UML class diagrams and feature models. Thus, the main contribution of this work is to provide an interoperability tool to generate software models (e.g.: class diagrams and feature models) from mind maps. This tool provides the capability of transformation between different industrial mind map tools (including cloud tools - SaaS) to different domain modelling tools, both class diagrams and for feature models. Finally, a case study was applied to verify this feasibility and check this interoperability assessment. The main contribution is MindDomain can be used in small projects for agile requirements modeling solutions.

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Correspondence to Fernando Wanderley .

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Ceballos, A., Wanderley, F., Souza, E., Cysneiros, G. (2016). MindDomain: An Interoperability Tool to Generate Domain Models Through Mind Maps. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9789. Springer, Cham. https://doi.org/10.1007/978-3-319-42089-9_33

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  • DOI: https://doi.org/10.1007/978-3-319-42089-9_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42088-2

  • Online ISBN: 978-3-319-42089-9

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